Category: optimization
#Frank-Wolfe #conditional gradient #convergence analysis
This blog post extends the convergence theory from the first part of my notes on the Frank-Wolfe (FW) algorithm with convergence guarantees on the primal-dual gap which generalize and strengthen the convergence guarantees obtained in the first part.
Category: optimization
#proximal splitting #three operator splitting #convergence analysis
I discuss a recently proposed optimization algorithm: the Davis-Yin three operator splitting.
Category: optimization
#Frank-Wolfe #conditional gradient #convergence analysis
This blog post is the first in a series discussing different theoretical and practical aspects of the Frank-Wolfe algorithm.
Category: optimization
#optimization #cheatsheet
Most proofs in optimization consist in using inequalities for a particular function class in some creative way. This is a cheatsheet with inequalities that I use most often. It considers …
Category: optimization
#optimization #asynchronous #SAGA
My friend Rémi Leblond has recently uploaded to ArXiv our preprint on an asynchronous version of the SAGA optimization algorithm.
The main contribution is to develop a parallel (fully asynchronous, no locks) variant of the SAGA algorighm. This is a stochastic variance-reduced method for general optimization, specially adapted for problems …
Category: optimization
#machine learning #hyperparameters #HOAG
TL;DR: I describe a method for hyperparameter optimization by gradient descent.
Most machine …
Category: software
#Python #scikit-learn #machine learning #lightning
Announce: first public release of lightning!, a library for large-scale linear classification, regression and ranking in Python. The library was started a couple of years ago by Mathieu Blondel who also contributed the vast majority of source code. I joined recently its development and decided it was about time for …
Category: software
#Python #scikit-learn #machine learning #lightning
Together with other scikit-learn developers we've created an umbrella organization for scikit-learn-related projects named scikit-learn-contrib. The idea is for this organization to host projects that are deemed too specific or too experimental to be included in the scikit-learn codebase but still offer an API which is compatible with scikit-learn and …
Category: misc
#Python #scikit-learn #machine learning #lightning
Recently I've implemented, together with Arnaud Rachez, the SAGA[1] algorithm in the lightning machine learning library (which by the way, has been recently moved to the new scikit-learn-contrib project). The lightning library uses the same API as scikit-learn but is particularly adapted to online learning. As for the SAGA …
Category: learning theory
#consistency #machine learning
My latests work (with Francis Bach and Alexandre Gramfort) is on the consistency of ordinal regression methods. It has the wildly imaginative …